UID:
almafu_9959328624902883
Umfang:
1 online resource (xi, 457 pages) :
,
illustrations
ISBN:
9780470723562
,
0470723564
,
9780470723555
,
0470723556
,
1281308331
,
9781281308337
Inhalt:
Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical methods do not have the power or flexibility to make sense of very large datasets, and symbolic data analysis techniques have been developed in order to extract knowledge from such data. Symbolic data methods differ from that of data mining, for example, because rather than identifying points of interest in the data, symbolic data methods allow the user to build models of the data and make predictions about future events. This book is the result of the work160; f a pan-European project team led by Edwin Diday following 3 years work sponsored by EUROSTAT. 160; It includes a full explanation of the new SODAS software developed as a result of this project. The software and methods described highlight the crossover between statistics and computer science, with a particular emphasis on data mining.
Anmerkung:
Cover -- TOC36;Contents -- Contributors -- Foreword -- Preface -- ASSO Partners -- Introduction -- CH36;1 The state of the art in symbolic data analysis58; overview and future -- Part I Databases versus Symbolic Objects -- CH36;2 Improved generation of symbolic objects from relational databases -- CH36;3 Exporting symbolic objects to databases -- CH36;4 A statistical metadata model for symbolic objects -- CH36;5 Editing symbolic data -- CH36;6 The normal symbolic form -- CH36;7 Visualization -- Part II Unsupervised Methods -- CH36;8 Dissimilarity and matching -- CH36;9 Unsupervised divisive classification -- CH36;10 Hierarchical and pyramidal clustering -- CH36;11 Clustering methods in symbolic data analysis -- CH36;12 Visualizing symbolic data by Kohonen maps -- CH36;13 Validation of clustering structure58; determination of the number of clusters -- CH36;14 Stability measures for assessing a partition and its clusters58; application to symbolic data sets -- CH36;15 Principal component analysis of symbolic data described by intervals -- CH36;16 Generalized canonical analysis -- Part III Supervised Methods -- CH36;17 Bayesian decision trees -- CH36;18 Factor discriminant analysis -- CH36;19 Symbolic linear regression methodology -- CH36;20 Multi45;layer perceptrons and symbolic data -- Part IV Applications and the SODAS Software -- CH36;21 Application to the Finnish44; Spanish and Portuguese data of the European Social Survey -- CH36;22 Peoples life values and trust components in Europe58; symbolic data analysis for 2022 countries -- CH36;23 Symbolic analysis of the Time Use Survey in the Basque country -- CH36;24 SODAS2 software58; Overview and methodology -- IDX36;Index -- Last Page.
Weitere Ausg.:
Print version: Symbolic data analysis and the SODAS software. Chichester, England ; Hoboken, NJ : J. Wiley & Sons, ©2008 ISBN 9780470018835
Weitere Ausg.:
ISBN 0470018836
Sprache:
Englisch
Schlagwort(e):
Electronic books.
;
Electronic books.
;
Electronic books.
DOI:
10.1002/9780470723562
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470723562
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470723562
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470723562
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